Apr 03, 2014

Making a decision? Check the data.

Working in a data-driven business culture is a jargon-y way of saying, “We use science to decide what to do to reach our desired outcomes at work.” Science is, at core, a method of logical inquiry and testing. The scientific method starts with a hypothesis – a hunch or a guess at what makes something happen. The rest of science is testing and analysis: Is the hunch the cause of the outcome? Is it the only cause? Is something else happening? If you have a hunch in science, you test it to see if it’s true.

Data-driven business culture applies the scientific method to business decision making. It’s an alternative to gut-instinct and “Highest Paid Person’s Opinion” decision making, bereft of hunches, feelings, instincts, and personal preferences. Management must support this methodology, decision-makers must have the knowledge required to use the data as input and feedback on their projects, and the data must provide reliable insights on which to stake business decisions.

Management Support

In a data-driven business, executives believe that their organization’s success is based on doing the right things to achieve a measurable outcome.

We have leadership support already from some parts of the BBG for web analytics – some editors set targets for their traffic and are evaluated on how well they meet those targets. At a strategic level, the BBG has emphasized establishing a set of key performance indicators (KPIs) that illustrate the impact the BBG has in target markets. Having these clear targets in mind lets everyone determine the most effective method toward achieving their goals, including identifying products that do not yield adequate results.

Education

In a data-driven culture, decision makers base their choices on evidence rather than hunches. They work towards targets, using metrics that tell them whether or not their project (or article or affiliation) is successful.

Here’s an example of turning a gut-based decision into a data-driven one:

Not data-driven: “I’m going to start a podcast about environmental issues because my boss told me to make a podcast about something, and I think I have enough to say about environmental issues.”

Data-driven (note the evidence, hypotheses, and goals): “I’ve noticed that we get lots of comments and questions about environmental issues when we include them in our general interest programs. Environmental articles get 100,000+ pageviews over several weeks after I post them, 30% of which are from one target country, so I infer that environmental issues are evergreen and have broad appeal AND specific reach in a target area. Any podcast we promote gets at least 45,000 downloads per episode, 40% of which are from that target country. I think that there’s an audience for an evergreen podcast just focusing on environmental issues, and I expect that if I promote it in regular programming and on related articles, it could get at least 30,000 downloads per episode after 2 months of publishing them weekly.”

Reliable Data

Trustworthy and readily available data fuels the data-driven decision-making process; data must be reliable, and stakeholders must review and analyze results regularly. In order to ensure BBG’s web analytic data are reliable, we’re undergoing an initial audit of our setup, and will have maintenance audits to make sure data continues to measure activity in our target regions precisely and correctly.

Strong, relevant data on its own will not yield results. In a data-driven business culture, everyone is attuned to their data on a regular and systematic basis so they can identify outliers and trends over time. The most effective decision-makers make a habit of monitoring their data, making changes to their projects in accordance with what they think will improve performance, and then observing if these changes caused the outcome they hoped for. Decision-makers who do not look at the data throughout their project’s lifespan forgo the opportunity to improve based on the feedback they could be getting.

Note: Much of this blog post was inspired by the University of British Columbia: Creating a Data Driven Business Culture, taught by Anil Batra.